Journal Article Archives - Page 56 of 66

Critique And Contribute: A Practice-based Framework For Improving Critical Data Studies And Data Science

Neff, Gina; Tanweer, Anissa; Fiore-Gartland, Brittany; Osburn, Laura. (2017). Critique and Contribute: A Practice-Based Framework for Improving Critical Data Studies And Data Science. Big Data, 5(2), 85 – 97.

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Abstract

What would data science look like if its key critics were engaged to help improve it, and how might critiques of data science improve with an approach that considers the day-to-day practices of data science? This article argues for scholars to bridge the conversations that seek to critique data science and those that seek to advance data science practice to identify and create the social and organizational arrangements necessary for a more ethical data science. We summarize four critiques that are commonly made in critical data studies: data are inherently interpretive, data are inextricable from context, data are mediated through the sociomaterial arrangements that produce them, and data serve as a medium for the negotiation and communication of values. We present qualitative research with academic data scientists, data for good projects, and specialized cross-disciplinary engineering teams to show evidence of these critiques in the day-to-day experience of data scientists as they acknowledge and grapple with the complexities of their work. Using ethnographic vignettes from two large multiresearcher field sites, we develop a set of concepts for analyzing and advancing the practice of data science and improving critical data studies, including (1) communication is central to the data science endeavor; (2) making sense of data is a collective process; (3) data are starting, not end points, and (4) data are sets of stories. We conclude with two calls to action for researchers and practitioners in data science and critical data studies alike. First, creating opportunities for bringing social scientific and humanistic expertise into data science practice simultaneously will advance both data science and critical data studies. Second, practitioners should leverage the insights from critical data studies to build new kinds of organizational arrangements, which we argue will help advance a more ethical data science. Engaging the insights of critical data studies will improve data science. Careful attention to the practices of data science will improve scholarly critiques. Genuine collaborative conversations between these different communities will help push for more ethical, and better, ways of knowing in increasingly datum-saturated societies.

Keywords

Big; Communication; Politics; Critical Data Studies; Data For Good; Data Science; Ethics; Qualitative Methods; Theory

In Situ Measurement of Wind Pressure Loadings on Pedestal Style Rooftop Photovoltaic Panels

Bender, W.; Waytuck, D.; Wang, S.; Reed, D. A. (2018). In Situ Measurement of Wind Pressure Loadings on Pedestal Style Rooftop Photovoltaic Panels. Engineering Structures, 163, 281 – 293.

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Abstract

The installation of rooftop photovoltaic (PV) arrays is increasing throughout the US. Until recently, pedestal type PV framing systems for rooftops were basically designed using procedures from the ASCE7-10 Components and Cladding Standard for rooftop equipment. The 2011 Japanese Standard Load design guide on structures for photovoltaic arrays was useful in characterizing the pressure coefficients on rooftops, but the Standard employs different wind speed and importance factors, making its use in the US quite limited, Even the updated 2017 version is written for a different audience. Because rooftop pressure loadings are high due to flow separation, SEAOC and other organizations contracted boundary layer wind tunnel tests of panels attached to rooftops to ascertain if the ASCE7-10 equipment loadings were appropriate. The investigations resulted in new standards for pedestal-style arrays that appear in Chapter 29 of ASCE7-16. However, the new standards are limited to simple geometries and orientations, and the dynamics of the simply-supported thin PV plates do not appear to be considered. Questions regarding the ability of the boundary tunnels to simulate accurately the turbulence at the scale required for the attached panels have been raised. In response, very limited full-scale investigations in large-scale tunnels and in situ have been undertaken to calibrate the tunnel results. The results of this paper represent one of these calibration investigations. Specifically, in situ full-scale net wind pressure loadings on a rooftop PV array in a pedestal-style framing system located on the three story Hogue Technology Building of Central Washington University (CWU) in Ellensburg, Washington were measured. The CWU campus has a rural setting in a region with steady winds: Ellensburg is located in the Kittitas Breezeway portion of the Northwest wind power region. Indeed, the Wild Horse Wind and Solar Farm is located on the outskirts of town. The data described here were collected from April through August 2014. The measured net pressure coefficient time series were similar to those for rooftop pressure loadings for low-rise buildings described in the literature such as the Wind Engineering Research Field Laboratory at Texas Tech University (Ham and Bienkiewicz, 1998 [1]; Levitan and Mehta, 1992 [2]). The analysis of the net pressure time series data included an examination of the minimum, maximum, mean, and RMS values. Preliminary results suggest that the range of the values is larger than assumed in the ASCE7 Standard, and that the magnitude of the loadings vary considerably spatially over the multiple panel array. The pressure loading measurements are ongoing.

Keywords

Building Integrated Photovoltaics; Buildings (structures); Calibration; Design Engineering; Pressure Measurement; Roofs; Solar Cell Arrays; Standards; Time Series; Turbulence; Wind Tunnels; Japanese Standard Load Design Guide; Wind Pressure Loading Measurements; Asce7-10 Components-cladding Standard; Tunnel Calibration; Texas Tech University; Kittitas Breezeway Portion; Wild Horse Wind And Solar Farm; Ellensburg; Central Washington University; Hogue Technology Building; Boundary Layer Wind Tunnel Test; Flow Separation; Multiple Panel Array; Wind Engineering Research Field Laboratory; Net Pressure Coefficient Time Series; Northwest Wind Power Region; Pedestal-style Framing System; Pv Plates; Rooftop Equipment; Pedestal Style Rooftop Photovoltaic Panels; Solar-arrays; Loads; Simulation; Wind Engineering; Photovoltaic Modules; Solar Energy; Full-scale Measurements; Wind Loadings; Photovoltaic Cells; Roofing; Wind Power; Structural Engineering; Boundary Layers; Cladding; Wind Tunnel Testing; Solar Cells; In Situ Measurement; Framing; Photovoltaics; Engineering Research; Wind Measurement; Pressure; Panels; Wind Pressure; Design Standards; Fluid Dynamics; Low Rise Buildings; Colleges & Universities; Wind Speed; United States--us

Physical and Mental Health Impacts of Household Gardens in an Urban Slum in Lima, Peru

Korn, Abigail; Bolton, Susan M.; Spencer, Benjamin; Alarcon, Jorge A.; Andrews, Leann; Voss, Joachim G. (2018). Physical and Mental Health Impacts of Household Gardens in an Urban Slum in Lima, Peru. International Journal Of Environmental Research And Public Health, 15(8).

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Abstract

Rural poverty and lack of access to education has led to urban migration and fed the constant growth of urban slums in Lima, Peru. Inhabitants of these informal settlements lack land rights and access to a public water supply, resulting in poor sanitation, an inability to grow food, and suboptimal health outcomes. A repeated measures longitudinal pilot study utilizing participatory design methods was conducted in Lima between September 2013 and September 2014 to determine the feasibility of implementing household gardens and the subsequent impact of increased green space on well-being. Anthropometric data and a composite of five validated mental health surveys were collected at the baseline, 6-months, and 12-months after garden construction. Significant increases from the baseline in all domains of quality of life, including: physical (p < 0.01), psychological (p = 0.05), social (p = 0.02), environmental (p = 0.02), and overall social capital (p < 0.01) were identified 12 months after garden construction. Life-threatening experiences decreased significantly compared to the baseline (p = 0.02). There were no significant changes in parent or partner empathy (p = 0.21), BMI (p = 0.95), waist circumference (p = 0.18), or blood pressure (p = 0.66) at 6 or 12 months. Improved access to green space in the form of a household garden can significantly improve mental health in an urban slum setting.

Keywords

Of-life Assessment; Psychometric Properties; Threatening Experiences; Vegetable Consumption; Developing-countries; Community Garden; Climate-change; Green Space; Poverty; Participation; Mental Health; Peru; Quality Of Life; Urban Slum; Social Capital

Why Neighborhood Park Proximity Is Not Associated with Total Physical Activity

Stewart, Orion T.; Moudon, Anne Vernez; Littman, Alyson J.; Seto, Edmund; Saelens, Brian E. (2018). Why Neighborhood Park Proximity Is Not Associated with Total Physical Activity. Health & Place, 52, 163 – 169.

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Abstract

This study explored how parks within the home neighborhood contribute to total physical activity (PA) by isolating park-related PA. Seattle-area adults (n = 634) were observed using time-matched accelerometer, Global Positioning System (GPS), and travel diary instruments. Of the average 42.3 min of daily total PA, only 11% was related to parks. Both home neighborhood park count and area were associated with park-based PA, but not with PA that occurred elsewhere, which comprised 89% of total PA. This study demonstrates clear benefits of neighborhood parks for contributing to park-based PA while helping explain why proximity to parks is rarely associated with overall PA.

Keywords

Physical Activity; Parks; Urban Planning; Environmental Health; Global Positioning System; Built Environment; Green Space; Recreation; Social Determinants Of Health; Health Research; Accelerometer Data; Self-selection; United-states; Public Parks; Older Women; Walking; Adults; Facilities

Estimating Traffic Volume for Local Streets with Imbalanced Data

Chen, Peng; Hu, Songhua; Shen, Qing; Lin, Hangfei; Xie, Chi. (2019). Estimating Traffic Volume for Local Streets with Imbalanced Data. Transportation Research Record, 2673(3), 598 – 610.

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Abstract

Annual average daily traffic (AADT) is an important measurement used in traffic engineering. Local streets are major components of a road network. However, automatic traffic recorders (ATRs) used to collect AADT are often limited to arterial roads, and such information is, therefore, often unavailable for local streets. Estimating AADT on local streets becomes a necessity as local street traffic continues to grow and the capacity of arterial roads becomes insufficient. A challenge is that an under-represented sample of local street AADT may result in biased estimation. A synthetic minority oversampling technique (SMOTE) is applied to oversample local streets to correct the imbalanced sampling among different road types. A generalized linear mixed model (GLMM) is employed to estimate AADT incorporating various independent variables, including factors of roadway design, socio-demographics, and land use. The model is examined with an AADT dataset from Seattle, WA. Results show that: (1) SMOTE helps to correct imbalanced sampling proportions and improve model performance significantly; (2) the number of lanes and the number of crosswalks are both positively associated with AADT; (3) road segments located in areas with a higher population density or more mixed land use have a higher AADT; (4) distance to the nearest arterial road is negatively correlated with AADT; and (5) AADT creates spatial spillover effects on neighboring road segments. The combination of SMOTE and GLMM improves the estimation accuracy on AADT, which contributes to better data for transportation planning and traffic monitoring, and to cost saving on data collection.

Keywords

Average; Prediction; Network; County

Spatial Relationships between Urban Structures and Air Pollution in Korea

Jung, Meen Chel; Park, Jaewoo; Kim, Sunghwan. (2019). Spatial Relationships between Urban Structures and Air Pollution in Korea. Sustainability, 11(2).

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Abstract

Urban structures facilitate human activities and interactions but are also a main source of air pollutants; hence, investigating the relationship between urban structures and air pollution is crucial. The lack of an acceptable general model poses significant challenges to investigations on the underlying mechanisms, and this gap fuels our motivation to analyze the relationships between urban structures and the emissions of four air pollutants, including nitrogen oxides, sulfur oxides, and two types of particulate matter, in Korea. We first conduct exploratory data analysis to detect the global and local spatial dependencies of air pollutants and apply Bayesian spatial regression models to examine the spatial relationship between each air pollutant and urban structure covariates. In particular, we use population, commercial area, industrial area, park area, road length, total land surface, and gross regional domestic product per person as spatial covariates of interest. Except for park area and road length, most covariates have significant positive relationships with air pollutants ranging from 0 to 1, which indicates that urbanization does not result in a one-to-one negative influence on air pollution. Findings suggest that the government should consider the degree of urban structures and air pollutants by region to achieve sustainable development.

Keywords

Land-use Regression; Particulate Matter Concentrations; Nitrogen-dioxide; Temporal Variations; Smart City; Quality; Health; Pm10; Fine; Pollutants; Urban Structure; Air Pollution; Moran's I; Bayesian Spatial Model; Motivation; Population; Urbanization; Nitrogen Oxides; Urban Structures; Emissions; Regression Analysis; Regression Models; Sulfur; Spatial Dependencies; Environmental Impact; Outdoor Air Quality; Metropolitan Areas; Economic Growth; Photochemicals; Industrial Areas; Urban Areas; Industrial Plant Emissions; Particulate Emissions; Particulate Matter; Data Analysis; Bayesian Analysis; Sustainable Development; Sulfur Oxides; Regions; Mathematical Models; Cities; China

A Roadmap for Urban Evolutionary Ecology

Rivkin, L. Ruth; Santangelo, James S.; Alberti, Marina; Aronson, Myla F. J.; De Keyzer, Charlotte W.; Diamond, Sarah E.; Fortin, Marie-josee; Frazee, Lauren J.; Gorton, Amanda J.; Hendry, Andrew P.; Liu, Yang; Losos, Jonathan B.; Macivor, J. Scott; Martin, Ryan A.; Mcdonnell, Mark J.; Miles, Lindsay S.; Munshi-south, Jason; Ness, Robert W.; Newman, Amy E. M.; Stothart, Mason R.; Theodorou, Panagiotis; Thompson, Ken A.; Verrelli, Brian C.; Whitehead, Andrew; Winchell, Kristin M.; Johnson, Marc T. J. (2019). A Roadmap for Urban Evolutionary Ecology. Evolutionary Applications, 12(3), 384 – 398.

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Abstract

Urban ecosystems are rapidly expanding throughout the world, but how urban growth affects the evolutionary ecology of species living in urban areas remains largely unknown. Urban ecology has advanced our understanding of how the development of cities and towns change environmental conditions and alter ecological processes and patterns. However, despite decades of research in urban ecology, the extent to which urbanization influences evolutionary and eco-evolutionary change has received little attention. The nascent field of urban evolutionary ecology seeks to understand how urbanization affects the evolution of populations, and how those evolutionary changes in turn influence the ecological dynamics of populations, communities, and ecosystems. Following a brief history of this emerging field, this Perspective article provides a research agenda and roadmap for future research aimed at advancing our understanding of the interplay between ecology and evolution of urban-dwelling organisms. We identify six key questions that, if addressed, would significantly increase our understanding of how urbanization influences evolutionary processes. These questions consider how urbanization affects nonadaptive evolution, natural selection, and convergent evolution, in addition to the role of urban environmental heterogeneity on species evolution, and the roles of phenotypic plasticity versus adaptation on species' abundance in cities. Our final question examines the impact of urbanization on evolutionary diversification. For each of these six questions, we suggest avenues for future research that will help advance the field of urban evolutionary ecology. Lastly, we highlight the importance of integrating urban evolutionary ecology into urban planning, conservation practice, pest management, and public engagement.

Keywords

Urban Ecology (biology); Climate Change; Urban Growth; Species Diversity; Urbanization; Citizen Science; Community Engagement; Eco-evolutionary Feedback; Gene Flow; Landscape Genetics; Urban Evolution; Urban Socioecology; Mouse Peromyscus-leucopus; Rapid Evolution; Population Genomics; Selection; Habitat; Differentiation; Framework; Environments; Biodiversity; Eco-evolutionary Feedback

Rebaselining Asset Data for Existing Facilities and Infrastructure

Abdirad, Hamid; Dossick, Carrie Sturts. (2020). Rebaselining Asset Data for Existing Facilities and Infrastructure. Journal Of Computing In Civil Engineering, 34(1).

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Abstract

This paper introduces rebaselining as a workflow for collecting reliable and verifiable asset management data for existing facilities and infrastructure. Reporting on two action research case studies with two public owners in the US, this research structures rebaselining in four phases: (1) preparing technology enablers, (2) collecting data from existing documents, (3) conducting field verification, and (4) updating asset management databases. These workflows address some of the common challenges in managing existing assets, including the fast-paced changes in asset data requirements, the inaccuracies in data and documentation of these existing assets portfolios, and the need to update data and documents over their life cycle. The findings set the groundwork for implementing workflow by mapping the rebaselining business processes in each phase, listing the technological requirements for these processes, and explaining the feasibility and examples of customizing building information modeling (BIM) platforms for rebaselining workflows. This customization of BIM platforms aims to offer simplified solutions that reduce the facility management staff's need for advanced BIM software knowledge.

Keywords

Asset Management; Building Management Systems; Business Data Processing; Database Management Systems; Facilities Management; Production Engineering Computing; Project Management; Risk Analysis; Software Tools; Reliable Asset Management Data; Verifiable Asset Management Data; Action Research Case Studies; Public Owners; Research Structures; Technology Enablers; Asset Management Databases; Facility Management Staff; Rebaselining Workflows; Technological Requirements; Rebaselining Business Processes; Existing Assets Portfolios; Documentation; Asset Data Requirements; Managing Existing Assets; Information; Bim; Existing Buildings; Infrastructure; Asset Data; Rebaselining

Dynamic Modal Accessibility Gap: Measurement and Application Using Travel Routes Data.

Guan, Jinping; Zhang, Kai; Shen, Qing; He, Ying. (2020). Dynamic Modal Accessibility Gap: Measurement and Application Using Travel Routes Data. Transportation Research: Part D, 81.

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Abstract

Accessibility is a key concept in transportation research and an important indicator of people's quality of life. With the development of big data analytics, dynamic accessibility that captures the temporal variations of accessibility becomes an important research focus. Few prior studies focus on comparative measures of dynamic accessibility to Points of Interest (POIs) by alternative travel modes. To fill this research gap, we propose a new index called dynamic modal accessibility gap (DMAG), which draws upon available data on residents' real travel routes using different travel modes, as well as the data on POIs. We study the DMAG in the real-travel covered area, assuming POIs are only useful if it is within someone's real-travel covered area. We then apply this DMAG methodology to Shanghai's central city and peripheral area. In both cases, we measure the accessibility for public and private travel modes. As an example, one-week taxi GPS and metro smart card data, and POIs data are used to generate the DMAG index for 30-minute and 60-minute trip durations for weekdays and holidays. Results show that DMAG can reflect the pattern of temporal variations. The proposed DMAG analytical framework, which can be applied at both the user and the system levels, can support urban and transportation planning, and promote social equity and livability.

Keywords

Air Travel; Choice Of Transportation; Urban Transportation; Transportation Planning; Urban Planning; Smart Cards; Inner Cities; Route Choice; Shanghai (china); Dynamic Accessibility; Modal Accessibility Gap (mag); Points Of Interest (pois); Public And Private Travel Modes; Temporal Variations; Scale Residential Areas; Transport; Time; Dimensions; Employment; Indicator; Choice; Boston; Car

Workforce Development: Understanding Task-Level Job Demands-Resources, Burnout, and Performance in Unskilled Construction Workers

Lee, Wonil; Migliaccio, Giovanni C.; Lin, Ken-Yu; Seto, Edmund Y. W. (2020). Workforce Development: Understanding Task-Level Job Demands-Resources, Burnout, and Performance in Unskilled Construction Workers. Safety Science, 123.

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Abstract

This study examines how task demands and personal resources affect unskilled construction worker productivity and safety performance. It extends the job demands-resources (JD-R) burnout model to show how job characteristics interact with burnout to influence performance. A modified model was designed to measure burnout, with exhaustion and disengagement among unskilled construction workers taken into consideration. An observational study was conducted in a laboratory environment to test the research hypotheses and assess the prediction accuracies of outcome constructs. Twenty-two subjects participated in multiple experiments designed to expose them to varying levels of task-demands and to record their personal resources as they performed common construction material-handling tasks. Specifically, both surveys and physiological measurements using wearable sensors were used to operationalize the model constructs. Moreover, partial least squares structural equation modeling was applied to analyze data collected at the task and individual levels. Exhaustion and disengagement exhibited different relationships with productivity and safety performance outcomes as measured by unit rate productivity and ergonomic behavior, respectively. Subjects with high burnout and high engagement showed high productivity but low safety performance. Thus, exhausted workers stand a greater chance of failing to comply with safety. As the sample and the task performed in the experiment do not cover the experience and trade of all construction workers, our findings are limited in their application to entry-level and unskilled workers, whose work is mainly manual material-handling tasks.

Keywords

Construction Workers; Structural Equation Modeling; Job Descriptions; Labor Productivity; Labor Supply; Burnout; Job Demand-resources Model; Partial Least Squares Structural Equation Modeling; Productivity; Safety; Wearable Sensors; Biomechanics; Construction Industry; Ergonomics; Occupational Health; Occupational Safety; Occupational Stress; Personnel; Statistical Analysis; Workforce Development; Understanding Task-level Job Demands-resources; Unskilled Construction Workers; Task Demands; Personal Resources; Unskilled Construction Worker Productivity; Job Demands-resources Burnout Model; Job Characteristics Interact; Exhaustion; Disengagement; Outcome Constructs; Varying Levels; Task-demands; Common Construction Material-handling Tasks; Physiological Measurements; Model Constructs; Individual Levels; Unit Rate Productivity; High Burnout; Low Safety Performance; Exhausted Workers; Entry-level; Unskilled Workers; Manual Material-handling Tasks; Heart-rate-variability; Labor Productivity Trends; Physiological Demands; Emotional Exhaustion; Safety Climate; Role Stress; Engagement; Fatigue; Workload; Task Analysis; Workforce; Level (quantity); Construction Materials; Personnel Management; Materials Handling; Multivariate Statistical Analysis